Data Analyst Intern

About Grexa AI

Grexa AI is a venture-backed startup on a mission to build the world’s first Marketing AI Platform for small businesses - a fully autonomous system that drives Real Revenue by automating and optimizing digital marketing.

Founded by 4 seasoned IIT alumni and former Testbook Founders / CXOs (scaled to $30Mn ARR business with 1,000+ employees, successfully acquired by a leading edtech company), the team brings deep product expertise, execution speed, and a track record of building at scale.

We’re funded, building fast, and assembling a high-performing team to disrupt the global digital marketing space from India. If you’re excited to solve real problems and build transformative AI products - this is your calling.

Role Overview

We are seeking a detail-oriented Data Analyst to support data-driven decision-making by building dashboards, automating workflows, and setting up ETL pipelines. This role requires strong analytical skills and a proactive mindset to enhance business processes.

Key Responsibilities

• Design and maintain dashboards to visualize key metrics.
• Conduct data analysis to uncover trends and insights for business decisions.
• Collaborate with cross-functional teams to understand data needs and deliver solutions.
• Work closely with the product, sales, and marketing team to align data strategies.
• Automate repetitive workflows and data processes.
• Develop and manage ETL pipelines for seamless data extraction, transformation, and loading.
  
  

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• Proven experience in data analysis.
• Experience in developing reports and dashboards in Metabase and Redash.
• Strong proficiency in writing advanced Mongo queries.
• Proficiency in Excel & Google App Script.
• Analytical thinking with a solid understanding of data mining techniques.
• Strong communication and collaboration skills, with the ability to effectively convey complex technical concepts to both technical and non-technical stakeholders.
  
  

Good to have: Experience working on Python for data processing and pipeline building using libraries such as Pandas, NumPy, and Matplotlib.